Computational Chemistry Lead
About the role
This role supports drug discovery efforts by applying advanced computational chemistry techniques to design and optimize small-molecule therapeutics. The position requires close collaboration with internal teams and external CROs to accelerate candidate selection and improve research productivity.
Responsibilities
Apply molecular modeling, docking, molecular dynamics, homology modeling, and structure-based design to guide compound optimization.
Use cheminformatics and machine learning tools to analyze SAR, ADME/Tox profiles, and predict compound behavior.
Develop generative models, reinforcement learning pipelines, and predictive analytics for compound design and optimization.
Curate chemical libraries, manage data pipelines, and support SAR/ADME analysis.
Serve as lead or co-lead in projects, setting project goals and defining plans.
Design novel compounds based on ADME and SAR principles; optimize lead molecules for potency, selectivity, and pharmacokinetics.
Data Analysis & Reporting: Analyze large datasets from simulations and experimental data with scientific rigor; interpret computational results and prepare detailed research reports and present findings internally and externally to technical and non-technical audiences.
Collaborate with medicinal chemists, biologists, and pharmacologists to guide compound progression from hit to lead.
Foster a collaborative, transparent, and creative team environment that drives innovation and invention.
Close partnership with colleagues in Japan is expected.
Explore and apply cutting-edge technologies and global scientific trends to enhance research capabilities.
Stay current with scientific literature and emerging technologies.
Manage team priorities and resources in alignment with the company's overall I-Lab strategy and objectives.
Oversee computational chemistry execution at CROs, including troubleshooting and performance enhancement.
Evaluate and onboard new CROs to improve cost-efficiency and research quality.
Maintain weekly communication and productivity tracking with CRO teams.
Qualifications
Ph.D. in Computational Chemistry, Cheminformatics, Medicinal Chemistry, or related field; or M.S. with 5+ years of industry experience.
Proven experience in computational support of small molecule drug discovery.
Familiarity with AI-driven drug design.
Proficiency in software packages such as Schrodinger, MOE, OpenEye, Rosetta, and scientific programming (Python, Pipeline Pilot).
Strong understanding of organic and synthetic chemistry concepts.
Experience managing CRO relationships and external collaboration.
Deep understanding of advancements in drug discovery, emerging technologies, and industry trends, and experience applying this knowledge to enhance research strategies.
Molecular Modeling & Simulation: Proficient in structure-based drug design (SBDD), including molecular docking, molecular dynamics (MD), and free energy perturbation (FEP).
Skilled in homology modeling, pharmacophore modeling, and quantum mechanics/molecular mechanics (QM/MM) methods.
Experienced in cryptic pocket identification and virtual screening for challenging targets.
Chemoinformatics & Data Science: Applies cheminformatics tools to analyze structure-activity relationships (SAR), ADME/Tox profiles, and compound clustering.
Uses machine learning (ML) and AI-driven platforms for compound prioritization, generative design, and predictive modeling.
Familiar with scripting languages like Python and platforms such as Schrödinger, MOE, and KNIME.
Drug Discovery Integration: Designs and optimizes small molecules for potency, selectivity, and pharmacokinetics.
Skills
Strong collaboration and teamwork abilities.
Excellent oral and written communication in English.
Strategic thinking and problem-solving capabilities.
Strong communication and influencing skills.
A highly collaborative win-win mindset is essential.
Working Environment
This position is based in Cambridge, MA and will require on-site work.